ABSTRACT We propose a set of complementary family-based and population-based study designs and state-of- the-art genome resequencing techniques to map a set of asthma and COPD-associated sequence variants for airflow obstruction and assess their interrelationships and functional significance through the following specific aims: Specific Aim 1: We hypothesize that coding and regulatory variants for airflow obstruction overlap in asthma and COPD. In Subaim 1a, we will generate genome-wide SNP data (GWAS) in Costa Rica asthma pedigrees and combine this data with existing asthma and COPD genome-wide SNP data to perform a common variant meta-analysis. In Subaim 1b, we will perform whole genome sequencing in selected members of these extended pedigrees and perform extended pedigree rare variant analysis. This data will be combined with existing exome sequencing and genotyping in asthma and COPD in a rare variant meta-analysis. Further validation will be performed using genotyping in 2595 members of trios from Costa Rica. In Subaim 1c, we will perform an analysis combining information from common and rare variants in all available populations using gene-based and haplotype-based analyses. Specific Aim 2: We hypothesize that epistatic interactions underlie genomic complexity and we will elucidate those In Subaim 2a, we will use a molecular interaction network (interactome) to understand the genetic loci associated with airflow obstruction in asthma and COPD. We will evaluate whether genes from GWAS (from Aim 1 and Projects 2 and 3) are significantly connected via protein-protein interactions. In Subaim 2b, we will apply the Disease Module Detection method (DIAMOnD) that exploits the structural properties of the interactome to identify the disease module for airflow obstruction in asthma and COPD. In Subaim 2c, we will prioritize genes with rare, deleterious variants that demonstrate an association with airflow obstruction in Aim 1. interactions using a molecular interaction network (interactome) approach. Specific Aim 3: We hypothesize that the genetic loci and network modules associated with airflow obstruction will have functional molecular effects. Variants identified in Aim 1 will be assessed using our functional fine-mapping pipeline. Gene networks identified in Aim 2 will be validated by high-throughput shRNA knockdown experiments that will allow us to focus on hub genes with important lung function-associated genetic effects. Genes passing this validation will be examined for eQTLs in Project 2, and mQTL with Project 3 with additional promising regulatory variants chosen for functional fine mapping in our functional pipeline in Project 1.